hw {ACSWR} | R Documentation |
Height-Weight Covariance Study
Description
The data set highlights the importance of handling covariance when such information is available. If the covariance is not incorporated, hypothesis testing may lead to entirely difference conclusion.
Usage
data(hw)
Format
A data frame with 20 observations on the following 2 variables.
Height
the height of an individual
Weight
the weight of an individual
References
Rencher, A.C. (2002). Methods of Multivariate Analysis, 2e. J. Wiley.
Examples
data(hw)
sigma0 <- matrix(c(20, 100, 100, 1000),nrow=2)
sigma <- var(hw)
v <- nrow(hw)-1
p <- ncol(hw)
u <- v*(log(det(sigma0))-log(det(sigma)) + sum(diag(sigma%*%solve(sigma0)))-p)
u1 <- (1- (1/(6*v-1))*(2*p+1 - 2/(p+1)))*u
u;u1;qchisq(1-0.05,p*(p+1)/2)
[Package ACSWR version 1.0 Index]